In order to cope with the frequent unpredictable changes that may occur in manufacturing systems, and to optimize given performance criteria, the assignment of workers can be decided online in a dynamic manner, whenever the worker is released. Several studies, in the ergonomics literature, have shown that individuals' performances decrease because of their fatigue in work. In manufacturing context, the workers’ fatigue impacts the task durations. Therefore, we propose to solve the online workers assignment problem through a heuristic, which takes this workers' fatigue into consideration, so as to minimize the mean flowtime of jobs.

In this experiment, game theory was used to assess the interactions between three cell phenotypes usually found in cancer. The three defined cells were autonomous growth cells, invasive and motile malignant cells, and cells that performed anaerobic glycolysis. Based on preset variables in the payoff matrix, analytical equations were deduced that allowed for the analysis of the proportion of autonomous growth and malignant cells in a tumor. AnyLogic was also used to simulate the interactions between cancerous and normal cells.

One of the most common operations to any construction project is earthwork. In fact, most, if not all, construction projects begin with earthwork activities. These activities require heavy equipment, are generally quite costly and consume a considerable amount of time.

The objective of this paper is to propose and test a framework for integrated assessment of infrastructure systems at the interface between the dynamic behaviors of assets, agencies, and users. For the purpose of this study a hybrid agent-based/mathematical simulation model is created and tested using a numerical example related to a roadway network.

This research proposes and tests an integrated framework for bottom-up simulation of performance in construction projects. The proposed framework conceptualizes construction projects as systems-of-systems in which the abstraction and micro-simulation of dynamic behaviors are investigated at the base-level consisting of the following elements: human agents, information, and resources.

Modelling real workforce choices accurately via Agent Based Models and System Dynamics requires
input data on the actual preferences of individual agents. Often lack of data means that analysts can have
an understanding of how agents move through the system, but not why, and when.

Workers cross-trained with multiple tasks can improve the workforce flexibility for the plant to handle
variations in workload. Therefore, it is necessary to study the dynamic multi-skilled workforce planning
problem of production line with the application of cross-training method.

This paper discusses the development of a simulation model to mimic a return to work phenomenon of Social Security Disability Insurance (SSDI) enrollees in the United States. Agent Based and Bayesian Network methods are used within a multi-method simulation model to capture system conditions and enrollee behavior.

Agent-based modeling (ABM) has gained great popularity in recent years, especially in application areas where human behavior is important, because it opens up the possibility of capturing such behavior in great detail. Hybrid models which combine ABM with discrete-event simulation (DES) are particularly appealing in service industry applications.